O R I G I N A L A R T I C L E
Influence of different land uses on groundwater quality
in southern Portugal
Alexandra Marcha˜ Penha1,2•Anto´nio Chambel1,4• Martinho Murteira5• Manuela Morais1,2,3
Received: 27 January 2015 / Accepted: 15 September 2015 / Published online: 2 April 2016 Springer-Verlag Berlin Heidelberg 2016
Abstract In Alentejo region, southern Portugal, differ-ences in groundwater samples from six groundwater bodies covered with different land uses were analysed based on the monitoring plan of the Alqueva multi-purpose project, created in the sequence of the construction of the Alqueva Dam on the Guadiana River, in South Portugal. For most of the groundwater bodies there is a statistical significant difference between magnesium, sulphate, chloride, and phosphate. All of these ions are strongly correlated with land use management. Groundwater, where land is covered by olive groves, has high levels of electric conductivity, calcium, potassium, sulphate, and phosphate. Dry land crops are correlated with calcium, magnesium, chloride and consequently, electric conductivity, phosphates and sulphate. Vineyards are strongly correlated with high sul-phate and phossul-phate levels. This study clearly shows that different land uses within a certain groundwater body influence the water quality in a different way. Therefore, an appropriate soil management should be adjusted to each situation, taking into account the aquifer matrix and the overlying soil.
Keywords Groundwater Land use Groundwater quality
Introduction
Groundwater is an important natural resource and it repre-sents a crucial component for the socio-economic develop-ment of a country. Natural processes, such as original quality of infiltrating waters, water-soil-rock interaction, lithology, hydrogeological conditions, tidal fluctuations, seawater intrusion, and anthropogenic activities, including agricul-ture, industry and urban development, are essential to determine groundwater chemistry evolution (Pacheco and Van der Weijden1996,2002; Pacheco et al.1999; Adams et al.2001; Rademacher et al.2001; Guo and Wang2004; Van der Weijden and Pacheco2006; Aris et al.2007; Lin et al.2012). Natural groundwater quality is highly defined by the interaction of its physical and chemical components with the aquifer geologic context, since the contact time between water and rock is essential for its final natural quality (Duan et al.2002; Pacheco and Van der Weijden2012a,b;2014a, b). Besides the natural processes, groundwater can also be influenced by the change in land use pattern (Basnyat et al. 1999; Roth et al.1996, Stigter et al.2006). This is particu-larly evident in areas with land use conflicts (Valle Junior et al.2014). In sensitive hydrogeological settings, the effects of human activity can be determinant for the final ground-water quality and can even influence the natural geochemical processes (Pacheco and Szocs2006; Pacheco et al.2013). Chronic groundwater problems can be caused by widespread long-lasting and damaging inputs of pollutants due to unsuitable land use and poor land management (Lerner and Harris 2009). Depending on the type of aquifer, on its hydraulic parameters, on the length and characteristics of the
& Anto´nio Chambel achambel@uevora.pt
1 Instituto Cieˆncias da Terra (ICT), Po´lo da Universidade de E´ vora, Rua Roma˜o Ramalho no. 59, 7000-671 E´vora, Portugal
2 Laborato´rio da A´ gua, Universidade de E´vora, E´vora, Portugal 3 Departamento de Biologia, Universidade de E´ vora, E´vora,
Portugal
4 Departamento de Geocieˆncias, Universidade de E´ vora, Rua Roma˜o Ramalho, 59, 7000-671 E´ vora, Portugal 5 EDIA, Empresa de Desenvolvimento e Infraestruturas do
Alqueva SA, Beja, Portugal DOI 10.1007/s12665-015-5038-7
flow path and on the pollutant characteristics (e.g. mass, volume, viscosity, miscibility capacity), the movement from the point of infiltration at the land surface to the point of discharge can be measured in hours, days, months, years, decades or even centuries (Lerner and Harris2009). Agri-culture practices can be a cause of diffuse pollution, which extends across the landscape and infiltrates to the ground-water through the whole outcrops of the respective aquifer (Lerner and Harris2009). The uncontrolled use of pesticides and fertilizers, used to increase the agriculture production, has been reported to have a direct and negative impact on groundwater quality (Carpenter et al.1998; Griffith 2002; Kolpin1997; Matson1997). Therefore, control and evalua-tion of groundwater quality is decisive to ensure its adequate use (Vijith and Satheesh2007).
Climate changes will possibly reduce groundwater resources and worsen its quality in many regions before any land use and land management changes are being considered. Except for the littoral west, which is influenced by the Atlantic climate, the climatic conditions in southern Portugal are Mediterranean type. The precipitation occurs mainly during winter, when the temperatures are low, and very low levels of precipitation occur in summer, when the temperatures are high. Climate change projections for the Mediterranean region predict an increase in temperature, a decrease in pre-cipitation and an increase on the occurrence of extreme events, with deep impacts on stream flows, water table levels and riverine ecosystems (Santos et al.2014,2015). On the other hand, the Mediterranean region faces an increasing water demand for agriculture and tourism (Treidel et al.2012).
The Alqueva multi-purpose project (EFMA, in Por-tuguese) is located in Alentejo, a region with an area of approximately 30,000 km2 (nearly a third of continental Portugal). The EFMA was conceived in 1957 as part of the Alentejo Irrigation Plan, but it was only implemented in 2002, after the construction of the Alqueva dam on Guadiana River, which created a lake with a length of 83 km, a surface of 250 km2and a total water volume of 4150 hm3. It was created to hold a strategic position in the use of resources and to allow mainly the exploitation of existing agriculture potential in the region, aiming to achieve the following objectives: to establish a strategic water reserve to respond to current and future needs of the region; to ensure a regular water supply to the populations, industries and agriculture; to strengthen the capacity of existing reservoirs distributed throughout the territory; to provide a progressive change of the specialisation of agriculture in the south of the country, namely changing rain feed crops to irrigated crops, and also by changing the irrigation processes, where the wells that were erstwhile used for irrigation would be substituted by the water provided by this new artificial lake. Thus, the so-called cyclic recycling practices, which consist on the reuse of groundwater, is reduced. Finally, this project also intends to
slow the desertification processes, to revert the depopulation of the region, to contribute to control the effects of climate change, creating at the same time potential for tourism compatible with environmental preservation and the expansion and enhancement of economic activities (inhttp:// www.alqueva.com.pt/en/).
As part of that project, a monitoring plan to classify groundwater quality was implemented. The main purpose of this study was to perform a comparison between dif-ferent land uses and to identify the impact of those surface occupations on groundwater quality for different ground-water bodies across the Alentejo region.
Study area, geology and hydrogeology
of the region
The study area is located in southern Portugal (Alentejo region) and involves different groundwater bodies (Fig.1) covered by different land uses, covering an area of 1200 km2 of irrigation land. The climate in Alentejo region is Mediter-ranean type with very hot and dry summers with a frequent occurrence of droughts, sometimes in cycles of two to three consecutive years, as well as low levels of precipitation in summer. The maximum monthly average temperature is around 34C (in July) and the minimum is between 5 and 10C (in January) (SNIRH2012). Among other characteristic of the Mediterranean climate is the water scarcity, where the majority of the great river’s tributaries are temporary (Rosado and Morais2010). During the dry season, these systems are characterised by the interruption of the superficial flow or total loss of water, while the wet season is characterized by the occurrence of flash floods (Gasith and Resh1999). Even so, the flow continues underground on the majority of these hydraulic systems. During summer, the annual precipitation is about 4 to 5 % of the total and the rainy season occurs during late autumn, winter and early springtime. The mean annual precipitation in Alentejo region ranges from 450 to 1000 mm and it is irregularly distributed throughout the year and among different years. Therefore, the agriculture requires intensive watering due to high evapotranspiration during the productive cycle. The dry and wet cycles have a major role in the structure and functioning of Mediterranean ecosystems. In the south part of the country, the disrupting of the superficial river runoff during the hottest months interferes in the variation of water levels in reservoirs, usually followed by a decrease in water quality. On the other hand, flash flood events increase the nutrient and organic matter loads that reach downstream reservoirs (Silva et al.2011).
The study area is within the geologically complex Ossa-Morena Zone (OMZ), a part of the Iberian Peninsula hard rocks known as the Old Massif. The OMZ is formed by Palaeozoic metamorphic and igneous rocks. The
metamorphic rocks are represented mainly by schists, shales, greywackes, quartztites, gneisses, charnockites, amphibolites, metamorphised volcanic rocks, and meta-morphic limestones, in a great complexity, affected in some places by strong structural features, making difficult the geological interpretation of the area. The lithology of the igneous rocks varies from granites to granodiorites, quartz-diorites, tonalitic rocks, diorites, gabbros, andesites, etc. (Chambel et al.2007). Both the water volume and the natural water quality in the aquifers depend on the mineral composition of the rocks and on the fractured pattern and are also directly associated with the dimension of the weathering layers in the area: the most basic rocks (e.g. gabbros) have generally the most deep weathered layers (Chambel et al. 2007). On the western border of the Palaeozoic massif, the study also considered a sedimentary basin (Basin of Alvalade) deposited in Tertiary times over the metamorphic and igneous rocks of the Old Massif.
The study involved six groundwater bodies, four of them being defined as aquifers in hard rocks (E´ vora, Cuba-S.
Cristo´va˜o, Vidigueira-Selmes and the Gabbros of Beja aquifers), one defined as a low productivity hydrogeolog-ical hard rock sector (Old massif) and one (the Basin of Alvalade) a sedimentary basin deposited over the western border of the Palaeozoic massif. This last one, involving a sedimentary aquifer is here considered in its broader geo-logic sense, once the border considered in this study involves areas where groundwater is sometimes scarce and has normally natural chemical problems for its use (brackish water) and also areas of more productivity and better quality. Table1shows the more important lithologic types of these six groundwater bodies.
Table2 shows the main hydrochemical differences between the aquifers and hydrogeologic sectors defined in Table1. The main difference is between the hard rock aquifers and the hydrogeological sector (Old Massif) by one side and the Basin of Alvalade aquifer by other side. As can be seen in Table 2, the average of Electric Con-ductivity (EC) of groundwater in the Basin of Alvalade is more than three times the average of any other of the
Fig. 1 Map of the study area in Portugal showing the location of the groundwater bodies and the sampling points with the corresponded type of land use
aquifers, and this reflects mainly the sodium-chloride content of the waters of this aquifer, which are, in the border of the Basin, sometimes highly saline.
In the Piper diagram of Fig.2, and using only the average of all the water samples collected in each one of the systems in a previous study (ERHSA2001), it’s clear that the Basin of Alvalade is completely different from the other aquifers and hydrogeological sectors, showing mainly sodium-chloride waters, in contrast with the other systems, where bicarbonates are the main anions and where the cations are present in much more similar percentages. Even so, it’s possible to see that also the Gabbros of Beja have a slightly different average composition from the other aquifer systems, with higher bicarbonate and slightly higher calcium-magnesium content. This is due to the more basic rocks of this system, which also reflects in a deeper weathered layer (30–40 m), creating in the area some of the best agriculture soils in Portugal.
Materials and methods
Land use, sample collection and laboratory analysis
Seventy-nine wells distributed in a part of the irrigation area of EFMA Project were selected for this study during
the monitoring program, according to the location defined in Fig.1. During the monitoring program, an inventory of the land use around each sampling point was organized. Five major types of land uses were identified: irrigated crops, dry land crops (rain feed crops), vegetable and fruit farms, olive groves and vineyards.
The sampling campaign was performed between March 2010 and July 2013, with 2 to 3 collections per year for each well during the dry and wet seasons. The sample collection was performed according to the ISO-5667 for Water Quality Sampling. Most of the groundwater samples were collected from open wells, bore holes and hand pumped at various depths. The water collection was per-formed using a 3 L Van d’Orn bottle (Wild Co, Australia), to about one meter below the groundwater level, trans-ferred to 1L polyethylene bottles and stored in portable refrigerators until they reached the laboratory. Water stored in the wells was not abstracted before taken the sample, except for the drilled wells, where this can have happened in some of them, depending on their storage capacity, and when water was abstracted using water pumps installed in the wells.
Twelve physical–chemical variables were chosen as more relevant for groundwater quality assessment: pH, electrical conductivity (EC), ammoniacal nitrogen (AN), total hardness (CaCO3), cations (Na?, K?, Ca2? and Table 1 Lithologic types of the six groundwater bodies identified in the area of study (Almeida et al.2000; Chambel et al.2006,2007)
Groundwater bodies Lithologic types
Old Massif sector Mainly schists and greywackes, and different kinds of igneous rocks, granites, granodiorites, quartz-diorites, tonalites, quartz-diorites, andesites, some gabbros, but also volcanic or porphyritic rocks E´ vora aquifer Gneisses, migmatites, granodiorites and quartz-diorites
Cuba-S.Cristo´va˜o aquifer Gabbrodiorites, granitic ortogneisses, a metapelitic-psamitic sequence, leptinites, black quartzites, metabasites and ortogneisses
Vidigueira-Selmes aquifer Basic volcanites, granodiorites, gabbrodiorites, hornfels
Gabbros of Beja aquifer Gabbros, diorites, serpentinites, meta-trondhejmites, meta-basalts, flasergabbros, amphibolites, piroxenites, dunites and peridotites
Basin of Alvalade aquifer Conglomerates, clay, marls, sandy limestones, clay sandstones, coarse gravel Not all of the described lithologic types for each of the groundwater bodies are represented in the area of study
Table 2 Main physical–chemical characteristics of the five aquifer systems and less productive sector (Old Massif Sector) identified in the study area Groundwater bodies N pH (pH units) EC (lS/cm) Ca (mg/L) Mg (mg/L) Na (mg/L) K (mg/L) Cl (mg/L) HCO3 (mg/L) SO4 (mg/L) NO3 (mg/L)
Old Massif sector 688 7.27 766 55 37 53 2.0 103 244 34 40
E´ vora aquifer 48 7.47 964 68 44 72 4.2 98 292 53 79
Cuba-S. Cristo´va˜o aquifer 35 7.39 782 68 36 68 3.0 90 260 49 43
Vidigueira-Selmes aquifer 23 7.60 813 65 45 58 1.4 79 266 48 39
Gabbros of Beja aquifer 71 7.54 825 68 43 41 0.7 50 293 63 61
Basin of Alvalade aquifer 13 7.56 3171 104 116 273 7.3 824 387 80 32
Mg2?) and anions (NO3-, SO42-, PO43-and Cl-). In situ physical–chemical measurements (water temperature, pH and EC), were done using the in situ probe Troll 9500 Profiler XP (In-Situ Europe, UK). For major ions, the samples were acidified using 1 % HNO3to stabilize trace metals. The laboratory methods used to determine each variable and the respective reporting limits are summarized in Table3.
Data and statistical analysis
To analyse differences between groups and because the data are not normally distributed, the non-parametric Kruskal–Wallis test was used. The Kruskal–Wallis test is the non-parametric analogue of a one-way analysis of variance (one way ANOVA), which does not make sup-positions about normality. It assumes that populations have the same shape of distribution for the observations in each group. However, to be performed, the observations have to be ranked, just as most non-parametric tests. Therefore, the null hypothesis for the Kruskal–Wallis test involves that the samples are from identical populations (Hecke2012).
The purpose of this study was to evaluate if the land use influenced groundwater quality. Therefore, the following null hypothesis and questions were established:
1. Concentration of individual chemical variables does not differ between groundwater bodies.
2. Concentration of individual chemical variables does not differ between land uses within the respective groundwater body.
3. Concentration of individual chemical variables does not differ between wet and dry season for land uses within the respective groundwater body.
4. Concentration of individual chemical variables related to anthropogenic activities does not differ between hydrological years for land uses within the respective groundwater body.
To further evaluate progression in groundwater quality before and after the EFMA project, the limits defined by the Decree Law 306/2007 from August 27th for water supply use, were used to detect how many cases were in infringe-ment (Table3). These data were then compared with data provided by the national water resources information system (SNIRH, in Portuguese) and previously published results (Chambel et al.1999,2007; Fialho et al.1998).
A significance of 0.05, followed by a Bonferroni cor-rection as post hoc test, was used to identify differences between groundwater bodies, land uses and annual and seasonal changes. The results are represented in tables and box-and-whiskers graphs. 80 60 40 20 20 40 60 80 20 40 60 80 20 40 60 80 20 40 60 80 20 40 60 80 Ca Na+K HCO3 Cl Mg SO4 <= C a + M g Cl + SO4 => Piper Plot C C C O O O A A A D D D K K K M M M Legend Legend MVidigueira-Selmes
K Old Massif Sector
D Gabros of Beja
A Évora
O Cuba-S. Cristóvão
C Basin of Alvalade Fig. 2 Piper diagram of the
different aquifers and less productive hydrogeological sector (Old Massif). Original data from ERHSA (2001)
Results and discussion
From a natural point of view, groundwater quality reflects basically the water–rock interaction inside the aquifer. Even so, the natural groundwater quality also reflects the contribution of the quality of original infil-trating water and the interaction between water and soil in the unsaturated zone.
The chemical compounds also change overtime. Nor-mally they tend to increase with the water age inside the groundwater body (Morgenstern and Daughney 2012). The pH values increase overtime due to ongoing hydro-chemical reactions (Morgenstern and Daughney 2012). Therefore, under the dominance of carbonate dissolution or hydrolysis of silicates and providing that no significant secondary precipitation occurs, the older the water is inside the groundwater body, the more alkaline it becomes.
Apart from the natural groundwater hydrochemistry, mainly dependent on the equilibrium between water and rock, there is the referred influence of anthropogenic activities.
The descriptive statistics for the physical–chemical parameters determined in the groundwater samples are summarized in Table4. For each groundwater body, all the parameters exhibit a high distribution, suggesting a spatial variation, as indicated by the high standard deviation val-ues. These differences can be explained by the different land covers within the same groundwater body, which might interfere with the groundwater quality, but also by geologic or structural differences inside the aquifer or groundwater body.
Concentration of individual chemicals and groundwater bodies
To test if the individual chemical concentrations were different for each groundwater body, the Kruskal–Wallis test was performed without discriminating land covers within each groundwater body. The test results for question 1 (see ‘‘Data and statistical analysis’’ section) rejected the null hypothesis (Table5). Some chemicals occur naturally in groundwater but may be different from groundwater body to groundwater body due to the respective geology and weathering, and may occur at higher concentrations under certain land use. Interestingly, there were three parameters that were not different among the groundwater bodies, such as the ammoniacal nitrogen, phosphate and nitrate. Remarkably, these are some of the main variables related to land use management, mainly concerning fertil-izers application.
For example, a comparison between two of the ground-water bodies, the Old Massif sector and the Basin of Alvalade aquifer, shows a difference of 0.50 in pH units (Table4, Old Massif sector, mean = 7.58; Basin of Alva-lade aquifer, mean = 7.05). This difference is easily justi-fied by the mineralogical composition of each groundwater body, the Old Massif sector composed of shales, schists and other metamorphic or igneous rocks, while the Basin of Alvalade aquifer is a Tertiary sedimentary aquifer com-posed mainly by sandstone, conglomerate and gravel in the main productive units, formed by minerals much less sen-sitive to weathering than the ones of the other unities, like quartz. The low level of potassium in groundwater systems is due to its high capacity of cation exchange with the clay
Table 3 Methods used to determine the physical– chemical variables
Variable Units Limitsa Method
MRV MAV
Temperature C 12 25 Thermometric analysis
pH pH units 6.5–8.5 9.5 Electrometric analysis
Electrical conductivity lS/cm 400 1000 Electrometric analysis
Ammoniacal nitrogen mg/L NH4? 0.05 0.5 Indophenol blue method
Calcium mg/L Ca2? 100 – Volumetric analysis
Chlorides mg/L Cl- 25 250 Volumetric analysis
Total hardness mg/L CaCO3 – 500 Volumetric analysis
Phosphates mg/L PO43- 0.4 – Molecular absorption spectrophotometry
Magnesium mg/L Mg2? 30 50 Atomic absorption spectroscopy
Potassium mg/L K? 10 12 Atomic absorption spectroscopy
Sodium mg/L Na? 20 150 Atomic absorption spectroscopy
Nitrate mg/L NO3- 25 50 Molecular absorption spectrophotometry
Sulphate mg/L SO4- 25 250 Molecular absorption spectrophotometry
MRV maximum recommended value, MAV maximum admissible value a Limits according Decree Law 306/2007, August 27th
Table 4 Descriptive statistics for the different groundwater bodies and the different land uses Groundwater bodies and land uses N Variables and units
pH Electric
conductivity
Ammoniacal nitrogen
Calcium Chloride Total hardness
pH units lS/cm mg/L NH4? mg/L Ca2? mg/L Cl- mg/L CaCO3
Groundwater body
Old massif sector Mean ± SD min–max 254 7.58 ± 0.35 6.91–9.10 1042.1 ± 671.9 174.7–5410.0 0.13 ± 0.22 0.05–2.76 99.3 ± 34.7 12.0–231.0 133.7 ± 218.6 14.8–1900 430.6 ± 157.3 156.0–1357.0 E´ vora aquifer Mean ± SD
min–max 109 7.55 ± 0.40 6.83–8.90 803.9 ± 282.1 237.7–1778.0 0.12 ± 0.16 0.05–0.70 67.8 ± 23.1 31.6–137.0 71.5 ± 56.5 6.0–324.0 320.3 ± 85.2 181.0–562.0 Cuba-S. Cristo´va˜o aquifer Mean ± SD min–max 22 7.54 ± 0.37 7.0–8.3 935.4 ± 353.5 488.0–2090.0 0.09 ± 0.10 0.05–0.47 85.2 ± 20.6 47.0–118.0 66.5 ± 28.2 9.0–130.0 349.5 ± 89.2 186.0–449.0 Vidigueira-Selmes aquifer Mean ± SD min–max 70 7.52 ± 0.36 7.00–9.15 811.2 ± 183.0 439.2–1416.0 0.16 ± 0.27 0.05–1.76 91.8 ± 27.4 5.0–130.0 103.6 ± 162.8 29.4–1177.0 381.9 ± 80.1 203.0–579.0 Gabbros of Beja aquifer Mean ± SD min–max 206 7.60 ± 0.33 6.67–8.86 808.6 ± 356.9 252.1–2526.0 0.36 ± 1.70 0.05–19.70 88.4 ± 25.0 13.6–188.0 66.8 ± 79.2 10.0–724.0 383.9 ± 118.2 104.0–840.0 Basin of Alvalade aquifer Mean ± SD min–max 19 7.05 ± 0.64 6.09–8.20 500.7 ± 418.9 72.8–1303.0 0.21 ± 0.30 0.05–0.89 50.8 ± 39.5 11.1–98.0 68.0 ± 56.3 6.0–213.0 311.4 ± 223.0 37.0–603.0 Land use
Dry land crops Mean ± SD
min–max 235 7.57 ± 0.33 6.91–8.86 1064.4 ± 718.7 252.1–5410.0 0.34 ± 1.60 0.05–19.7 98.6 ± 35.9 12.0–231.0 131.6 ± 234.6 9.0–1900.0 426.9 ± 161.0 156.0–1357.0 Vegetables/fruit farm Mean ± SD min–max 130 7.54 ± 0.30 7.00–8.40 814.9 ± 254.4 397.0–1807.0 0.12 ± 0.18 0.05–1.28 89.3 ± 27.5 26.0–158.0 61.1 ± 37.2 11.0–237.0 374.7 ± 89.8 181.0–586.0 Irrigated crops Mean ± SD
min–max 43 7.63 ± 0.48 6.99–8.90 736.7 ± 156.3 482.0–1097.0 0.12 ± 0.17 0.05–0.66 67.8 ± 16.8 48.0–113.0 56.1 ± 14.5 28.6–75.0 317.3 ± 56.4 247.0–422.0
Olive grove Mean ± SD
min–max 242 7.55 ± 0.42 6.09–9.15 779.1 ± 299.0 72.8–1712.0 0.11 ± 0.17 0.05–1.58 85.3 ± 29.6 5.0–181.0 85.2 ± 99.2 6.0–1177.0 371.0 ± 136.6 37.0–903.0 Vineyard Mean ± SD min–max 30 7.56 ± 0.40 6.83–8.30 978.5 ± 392.8 527.9–1778.0 0.23 ± 0.51 0.05–2.76 75.5 ± 17.8 41.0–97.0 119.6 ± 89.6 14.0–324.0 378.9 ± 124.6 151.0–562.0 Groundwater bodies and land uses Variables and units
Phosphates Magnesium Nitrate Sodium Potassium Sulphate
mg/L PO43- mg/L Mg2? mg/L Na? mg/L K? mg/L NO3- mg/L SO4
-Groundwater body
Old massif sector Mean ± SD
min–max 0.35 ± 0.86 0.04–5.62 39.8 ± 22.8 10.0–211.0 82.0 ± 66.2 16.0–439.0 1.97 ± 1.65 0.18–8.65 28.9 ± 30.7 0.1–142.0 50.7 ± 40.3 5.0–254.0
E´ vora aquifer Mean ± SD
min–max 0.21 ± 0.24 0.04–1.16 45.2 ± 78.9 11.0–587.6 62.0 ± 40.9 5.0–241.0 3.93 ± 2.06 1.00–6.72 38.4 ± 52.2 0.25–215.00 75.6 ± 55.6 5.0–293.0 Cuba-S. Cristo´va˜o aquifer Mean ± SD
min–max 0.32 ± 0.37 0.04–1.19 31.6 ± 10.8 10.0–40.7 53.6 ± 42.9 9.0–126.0 2.22 ± 1.48 1.00–61.5 42.9 ± 54.6 1.5–190.0 61.8 ± 25.6 35.0–116.0 Vidigueira-Selmes aquifer Mean ± SD
min–max 0.51 ± 1.54 0.04–9.73 32.0 ± 10.7 13.1–56.3 46.8 ± 30.5 7.0–132.0 1.49 ± 1.35 0.24–5.01 29.5 ± 32.3 0.2–122.9 46.7 ± 19.7 10.0–117.0 Gabbros of Beja aquifer Mean ± SD
min–max 0.33 ± 0.79 0.01–6.29 33.4 ± 13.1 10.0–89.0 52.6 ± 44.1 7.0–261.0 2.98 ± 9.03 0.15–63.7 37.4 ± 43.9 0.1–276.0 54.6 ± 61.5 5.0–595.0 Basin of Alvalade aquifer Mean ± SD
min–max 0.14 ± 0.09 0.04–0.37 23.4 ± 20.1 4.9–52.3 47.2 ± 42.0 2.0–100.0 1.75 ± 0.67 0.47–2.60 17.5 ± 21.0 0.6–97.5 64.4 ± 85.1 5.0–250.0 Land use
Dry land crops Mean ± SD
min–max 0.49 ± 1.26 0.04–9.73 40.3 ± 23.8 13.1–211.0 80.9 ± 75.8 7.0–439.0 1.84 ± 1.88 0.15–8.65 33.5 ± 39.0 0.1–202.0 56.5 ± 40.5 5.0–254.0 Vegetables/fruit farm Mean ± SD
min–max 0.21 ± 0.45 0.04–3.94 33.5 ± 9.5 10.0–72.1 53.9 ± 26.3 11.0–126.0 4.45 ± 11.30 0.16–63.70 42.1 ± 49.0 0.1–276.0 60.4 ± 34.2 5.0–178.0
minerals in the soil or inside the aquifer. On the other hand, potassium can be part of fertilizers; therefore, it is not a reliable cation to correlate with land use. The majority of representative natural chemical compounds in groundwater (Ca2?, Na?, Mg2?, HCO3-) derives from the weathering of the silicate or carbonate minerals in the rocks like feldspars, plagioclases, biotite, amphiboles, calcite or dolomite. Cl-is a special ion present in the aquifers, since it is more related to sea spray (so it is frequent in groundwater near the cost), but it can also be present in the aquifers by being trapped inside the rocks when the rock formations were formed under sea water or under saline lacks. SO42-can be linked to metal minerals in the rocks, like pyrite (FeS2) or arsenopyrite (FeAsS), which are present in many meta-morphic rocks of South Alentejo.
Concentration of individual chemicals and land use
To understand how the different land uses can influence groundwater quality, each different land uses were
identified inside each groundwater body. This was done using the information of the field reports filled by the sampling technician during the monitoring plan. The non-parametric test results showed that some variables were different among land uses, rejecting, this way, the null hypothesis 2 (see ‘‘Data and statistical analysis’’ section, Table6). Based on the results, some variables were dif-ferent for 3 out of 6 of the groundwater bodies, such as EC, calcium, phosphates, potassium and sulphate. The EC values were different among the Old Massif sector, E´ vora and Basin of Alvalade aquifers, which can be explained by the different natural composition of groundwater in these different geological environments (see Table2).
One could not see the same result for the Gabbros of Beja aquifer, although there were the same land uses. This can be justified by the high rock dissolution and high grade of fracturing associated with gabbros weathering, allowing high permeability (Duque and Almeida1998), which natu-rally increases the EC levels independently of the land cover. Calcium, besides being part of the mineralogy of many rocks, can also be applied as lime to adjust the soil pH in agriculture areas. Based on the results, there is a correlation between calcium levels and dry land crops, as it is observed for the Cuba-S. Cristo´va˜o, Gabbros of Beja and Basin of Alvalade aquifers (Table6). The same result was not observed for the Old Massif sector, probably due to its high variety of rocks with high natural calcium content, and also because most part of the good agriculture lands are in the previous groundwater bodies and not in the Old Massif sector.
Besides those variables that change naturally overtime, there are some that have a conservative nature; therefore, significant changes for the conservative variables within each groundwater body could be directly correlated with differences between land uses. Chloride has a conservative nature and its transport mechanism by rain and sea spray is the main natural source (Morgenstern and Daughney 2012). Even so, in some areas of South Alentejo, there are also indications of salt retained during the formation of the rocks, being it in Palaeozoic times for the metamorphic
Table 4continued
Groundwater bodies and land uses Variables and units
Phosphates Magnesium Nitrate Sodium Potassium Sulphate
mg/L PO43- mg/L Mg2? mg/L Na? mg/L K? mg/L NO3- mg/L SO4
-Irrigated crops Mean ± SD
min–max 0.14 ± 0.07 0.04–0.36 34.1 ± 7.8 24.9–50.2 52.0 ± 20.6 11.0–72.1 4.20 ± 1.86 1.00–6.48 44.4 ± 59.3 0.28–215.0 43.5 ± 21.4 5.0–114.0
Olive grove Mean ± SD
min–max 0.27 ± 0.51 0.01–5.69 32.5 ± 14.4 4.9–78.5 57.9 ± 39.4 2.0–261.0 1.95 ± 1.5 0.28–6.70 29.0 ± 33.6 0.2–187.0 49.1 ± 61.1 5.0–595.0 Vineyard Mean ± SD min–max 0.44 ± 0.97 0.04–4.41 75.8 ± 15.0 21.7–77.9 84.8 ± 58.1 22.0–241.0 2.02 ± 1.71 0.40–5.85 29.6 ± 38.2 0.2–124.0 87.7 ± 70.9 21.0–293.0
Table 5 Kruskal–Wallis test results for differences between indi-vidual chemical concentrations between groundwater bodies
Variables for each groundwater body p values
pH 0.005 Electric conductivity \0.0001 Ammoniacal nitrogen 0.648 Calcium \0.0001 Chloride \0.0001 Total hardness \0.0001 Phosphates 0.597 Magnesium 0.035 Sodium \0.0001 Potassium \0.0001 Nitrate 0.238 Sulphate 0.017
rocks or in Terciary times for part of the sedimentary Basin of Alvalade aquifer, in this case by deposition of sea sed-iments (Costa et al.2003) or salt concentrated in salt lakes during arid climate times, mainly in the border of the basin (Chambel et al.2007).
Based on the results, along with the significant differ-ences in the chloride levels, there are also differdiffer-ences in the sulphate and phosphate concentration (Table6, Old Massif sector and E´ vora aquifer), indicating an agricultural source. Sulphate levels are highly correlated with vineyards, vegetables and fruit plants, as can be seen for all the groundwater bodies covered by vineyards (Old Massif sector, E´ vora and Gabbros of Beja aquifers, Table6) and vegetables/fruit farms (Old Massif sector, E´ vora and Cuba-S. Cristo´va˜o aquifers, Table6). Vegetables/fruit farms are also correlated with phosphate levels, which were different among 3 out of 6 groundwater bodies, except for the Gabbros of Beja aquifer. High levels of nitrate, sulphate, chloride and phosphorus can be related to fertilizer appli-cation such as ammonium sulphate, potassium chloride, potassium carbonate and other phosphorus compounds (Soveral Dias1999). It is common to use those chemicals in vineyards. Vineyards play an important role transferring
the total phosphorus to the water, since this element is not very mobile (Yang et al. 2009). Phosphorus is a macronutrient essential for the life of all living cells and is directly absorbed by the plants in the form of orthophos-phate (PO4
3-), which in turn is present in many fertilizers (Bowatte et al. 2006). Excessive use of these fertilizers may cause soil saturation, leading to an increase in phos-phorus transport through runoff by soil particles or through drainage, and consequently, transferred to groundwater.
In regions where sewage systems are lacking or do not cover the entire municipality, Cl-in groundwater may also be derived from leachates of domestic effluents (Pacheco 1998; Pacheco and Landim2005). The incorrect manage-ment of fertilizer applications as well as domestic effluents could lead to the increase of sulphate, phosphorus and chloride levels, contaminating groundwater but, in this region, with very low concentration of population, the problem of domestic effluents can happen just in specific points and can’t be considered at general level in the study area.
Magnesium ion is stable overtime (Morgenstern and Daughney 2012), therefore the significant differences observed could be directly correlated with land uses, since
Table 6 Results of Kruskall-Wallis test for the comparison of concentration of individual chemicals for each land use within the respective groundwater body
Groundwater body Veg/fruita oliveb dry landc vineyard Veg/fruit olive irrigatedd vineyard Veg/fruit dry land Olive dry land Veg/fruit olive dry land vineyard Olive dry land
Old Massif sector E´ vora aquifer Cuba-S. Cristo´va˜o aquifer Vidigueira-Selmes aquifer Gabbros of Beja aquifer Basin of Alvalade aquifer Land use for each groundwater body
Variables
pH 0.948 0.341 0.251 0.872 0.534 0.080
Electric conductivity 6.8E27 0.005 0.088 0.228 0.278 0.012
Ammoniacal nitrogen 0.093 0.985 0.793 0.735 0.117 0.089 Calcium 0.472 0.742 0.047 0.482 0.016 0.040 Chloride 0.020 8.65E26 0.088 0.929 0.409 0.162 Total hardness 0.711 0.824 0.144 0.305 0.176 0.040 Phosphates 0.032 0.001 0.004 0.541 0.383 0.453 Magnesium 0.005 0.407 0.347 0.732 0.395 0.040 Sodium 0.001 0.831 0.403 0.436 0.197 0.040 Potassium 9.12E25 0.029 0.117 0.820 0.620 0.040 Nitrate 0.125 0.134 0.061 0.167 0.379 0.764 Sulphate 0.005 0.001 0.465 0.747 0.049 0.079
Numbers in bold represent the p-values that are statistically different a Vegetables/fruit farm
b Olive grove c Dry land crops d Irrigated crops
some fertilizers can also contain magnesium in their composition. Both in the Old Massif sector and in the Basin of Alvalade aquifer, significant differences between land uses within the groundwater bodies were detected for magnesium levels, and both of them were correlated with dry land crops (Table6: magnesium levels, Kruskal– Wallis test, p value = 0.005; Table4: Old Massif sector, mean = 39.8 ± 22.8; Basin of Alvalade aquifer, mean = 23.4 ± 20.1).
Differences in nitrate levels at any of the groundwater bodies were not detected (Table6). One of the reasons could be the fact that nitrate, in spite of conservative, is not very stable and can vary for several reasons. It is also known that nitrates vary seasonally (Glavan et al.2013).
Concentration of individual chemical variables and seasonal variations
It should not be forgotten that there is a strong interaction between groundwater and surface water. Many rivers and streams are fed by springs, which make these rivers per-manent throughout the year, even when there is no rainfall. The rivers, in turn, may at some point of their journey contribute to recharge the aquifers (influent rivers). Thus, the poor quality sometimes occurs in surface waters can be transmitted to groundwater and vice versa (Ribeiro2009). By taking into account the average of physical–chemical parameters, the differences between wet and dry seasons can be masked. Therefore, the seasonal behaviour of each component was investigated (question 3, see ‘‘Data and statistical analysis’’ section). It is already known that during the wet season, surface water quality is primarily controlled by inorganic (mineral) contents and this non-anthropogenic form of pollution achieves high concentration in surface tributaries. Dissolved oxygen and pH represent the high importance of the surface runoff of nitrate, phosphorus and particulate organic matter. On the other hand, during the dry season, the system is mainly controlled by dissolved oxy-gen, pH and temperature (Serafim et al.2006). In this study, the null hypothesis was true for the Vidigueira-Selmes and for the Basin of Alvalade aquifers, where none of the parameters was influenced by wet and dry seasons at any type of land use (data not shown). Nevertheless, only a few variables were subject to changes with wet and dry seasons, such as pH, for vegetables/fruit farms at the Old Mas-sif sector, and at the Gabbros of Beja aquifer for olive grove and dry land crops. The same tendency was observed for vegetables/fruit farm at the Gabbros of Beja aquifer, although this difference was not significant (Kruskal–Wal-lis test, p = 0.053). These differences could not be corre-lated with any specific land use. Electric conductivity was also seasonally influenced for some land uses, but once again, it could not be correlated with any land use in
particular (Kruskal–Wallis test, Old Massif, olive grove, p = 0.003; E´ vora aquifer, vegetables/fruit farm and vine-yards, p = 0.030 and p = 0.045, respectively). The irriga-tion practices generally cause an increase in salts, due to alternating evapotranspiration cycles (Stigter et al. 2006). Therefore, some of the differences between land uses could be masked and not detected.
Concentration of individual chemical variables and anthropogenic activities
In mainland Portugal the diagnosis and characterization of groundwater quality done by the Management Plan of Hydrographic Basins (PGBH 2012) clearly showed that there are concentrations of nitrates from agricultural sour-ces in some aquifer systems, surpassing in many cases the parametric value of 50 mg/L (SNIRH2012). The increase of nitrate concentration in groundwater is a result, in most cases, of diffuse sources related to intensive use of fertil-izers in agricultural activities. The nitrogen compounds are found in soil in several states, in a dynamic equilibrium. In the presence of abundant organic matter and aerobic con-ditions, the processes of ammonification and nitrification cause mineralization of organic nitrogen to nitrate, which is the final and stable product of these reactions. Nitrate ion is very soluble in water and is absorbed by the soil, and it is easily leached by percolating water to the saturated zone (Ribeiro 2009). The leaching process of nitrogen occurs during wet periods of the year and after harvesting. Because nitrogen is not actively absorbed by the plants when precipitation exceeds evapotranspiration, during those periods the fertilizers and mineralized crop biomass residues are responsible by the nitrogen leaching to groundwater (Glavan and Pintar2010; Rusjan et al.2008). The leaching process of nitrate, from soil to ground-water, can be significantly reduced by good management practices. Even so, it will take many decades or even centuries for most nitrate concentrations to drop signifi-cantly, even if the nitrate leaching is stopped immediately (Lerner and Harris, 2009). Therefore, during the 4 hydro-logical years, a control of nitrate, phosphate and ammoni-acal nitrogen levels was performed, and differences along the years were calculated (question 4, ‘‘Data and statistical analysis’’ section).
Although a significant difference in nitrate content in all the groundwater bodies, except for the Old Massif sector and Gabbros of Beja aquifer (Kruskal–Wallis, p\ 0.0001, for both), the maximum levels achieved at the end of the hydrological year 2012/2013 were lower in all the groundwater bodies, compared with the first hydrological year studied (Fig.3). The reduction of nitrate levels could be explained by the fact that groundwater recycling is no longer in practice. Because of
the EFMA project, groundwater that was used before for irrigation is no longer used and it was substituted for water from the artificial lake, with approximately ten times less nitrate content (average of 33.07 ± 39.98 mg/L
NO3
-in groundwater from 2009 to 2013 for all wells studied, and 3.40 ± 7.00 mg/L NO3-in the surface water of the dam lake from March 2003 to September 2009, n = 237). 140 142 142 47 178 207 215 49 42 190 148 36 123 106 108 37 120 276 198 53 98 24 24 30 0 50 100 150 200 250 300 2009/2010 2010/2011 2011/2012 2012/2013 2009/2010 2010/2011 2011/2012 2012/2013 2009/2010 2010/2011 2011/2012 2012/2013 2009/2010 2010/2011 2011/2012 2012/2013 2009/2010 2010/2011 2011/2012 2012/2013 2009/2010 2010/2011 2011/2012 2012/2013 Old massif sector Évora aquifer Cuba-S. Cristóvao
aquifer Vidigueira-Selmes aquifer Gabbros of Beja aquifer Basin of Alvalade aquifer Nitrate levels (mg/L NO 3 -) Groundwater body p<0.0001 p<0.0001
Fig. 3 Differences in nitrate content in different hydrological years for the studied groundwater bodies. Numbers above upper whisker represent maximum levels reached
0.77 0.92 0.15 2.76 0.70 0.08 0.10 0.66 0.47 0.05 0.10 0.19 0.98 1.76 0.11 0.46 3.74 0.58 0.05 0.05 0.89 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 2009/2010 2010/2011 2011/2012 2012/2013 2009/2010 2010/2011 2011/2012 2012/2013 2009/2010 2010/2011 2011/2012 2012/2013 2009/2010 2010/2011 2011/2012 2012/2013 2009/2010 2010/2011 2011/2012 2012/2013 2009/2010 2010/2011 2011/2012 2012/2013 Old massif sector Évora aquifer Cuba-S. Cristóvao
aquifer Vidigueira-Selmes aquifer Gabbros of Beja aquifer Basin of Alvalade aquifer
Ammoniacal nitrogen levels (mg/L NH
4 +) Groundwater body p<0.0001 p<0.0001 p<0.0010 p=0.0020
Fig. 4 Differences in ammoniacal nitrogen content in different hydrological years for the studied groundwater bodies. Numbers above upper whisker represent maximum levels reached
Oppositely, differences along the 4 hydrological years for ammoniacal nitrogen levels were statistically different for the Old Massif sector, E´ vora, Vidigueira-Selmes and Gabbros of Beja aquifers (Kruskal–Wallis test, p \ 0.0001, p\ 0.001, p = 0.002, p \ 0.0001, respectively). How-ever, basically for all the groundwater bodies, the maxi-mum levels at the end of the monitoring plan were higher than on the previous year (Fig.4). Ammoniacal nitrogen is an indicator of organic contamination. Therefore, organic sources such as agricultural waste or seasonal dieback vegetation (Burkartaus and Stoner2008) could have led to an increase of levels of ammoniacal nitrogen on its own.
During the 4 hydrological years, phosphate levels were significantly reduced in the Old Massif sector, Vidigueira-Selmes and Gabbros of Beja aquifers (Kruskal–Wallis test, p\ 0.0001 for all, Fig. 5). Nevertheless, besides the high variability, by the end of 2012/2013 the levels were lower compared with the previous years, except for the Basin of Alvalade aquifer. The concentration of total phosphorus in groundwater is not related to the geology, due to the scarcity of this compound in igneous and metamorphic rocks, requiring other sources, including anthropogenic
activities and degradation of organic matter (Menezes et al. 2014). The high value detected during the hydrological year of 2012/2013 was observed at a dry land crop field and perhaps it was a particular situation. The monitoring plan must continue to screen this situation.
Mitigation measures
According to Foster et al. (2002) the types of agricultural activity responsible for the most severe cases of diffuse contamination of groundwater are those related to large areas of monoculture. Traditional shifting cultivation, extensive grasslands and agro-ecosystems usually have a lower prob-ability of subsurface contamination (Menezes et al.2014). Therefore, an appropriate soil management should be adjusted to each situation, taking into account the aquifer matrix and the overlying soil. Furthermore, seasonal moni-toring is of particular importance in the southern semi-arid areas of Portugal, where streams are temporary, with dis-charges ranging from zero to high volumes during the dry and wet seasons, respectively. Consequently, tributaries are subjected to a great variability in the hydrologic regime and
5.29 5.62 5.34 4.41 0.93 1.16 1.02 0.90 0.31 1.19 1.05 0.51 9.73 0.63 0.20 1.36 5.54 4.20 6.29 1.61 0.12 0.04 0.04 0.37 0 1 2 3 4 5 6 7 8 9 10 11 2009/2010 2010/2011 2011/2012 2012/2013 2009/2010 2010/2011 2011/2012 2012/2013 2009/2010 2010/2011 2011/2012 2012/2013 2009/2010 2010/2011 2011/2012 2012/2013 2009/2010 2010/2011 2011/2012 2012/2013 2009/2010 2010/2011 2011/2012 2012/2013 Old massif sector Évora aquifer Cuba-S. Cristóvao
aquifer Vidigueira-Selmes aquifer Gabbros of Beja aquifer Basin of Alvalade aquifer Phosphates levels (mg/L PO 4 3-) Groundwater body p<0.0001 p<0.0001 p<0.0001 p=0.0210
Fig. 5 Differences in phosphate content in different hydrological years for the analyzed groundwater bodies. Numbers above upper whisker represent maximum levels reached
experience wide variability in physical, chemical and bio-logical parameters, affecting the reservoir’s function downstream (Morais1995; Morais et al.2004).
With the EFMA project the use of groundwater is highly reduced in this area; so, the increase in mineralisation due to groundwater recycling is no longer in practice. Thus, a dilution of certain physical–chemical parameters is happening.
To avoid the continuous contamination of groundwater in this new area of irrigation, some planning is necessary: • The use of the manual of good agriculture practices • The control of the additives that the soil really needs,
being it fertilizers, pH correctors or others
• The control of the excess of irrigation water, namely using software to control the water quantity during irrigation according the needs of humidity in the soil; The last point focus technology that is more and more used in South Portugal, where water is scarce and the need to control water quantity for irrigation is also an economic goal of the more modern farmers.
Final remarks
This study clearly showed that different land uses within a certain groundwater body influence the water quality.
It is shown that, in spite of the original differences in the chemical content of natural groundwater bodies in this region, where for example chloride is highly variable between mainly hard and sedimentary rocks, the influence of fertilizers in agriculture seems to have a major role in the final content of specific ions.
In fact, in most of groundwater bodies there is a statistical significant difference between magnesium, sulphate, chlo-ride, and phosphate. All of these ions are strongly correlated with land use management. Groundwater where land is covered by olive groves has high levels of EC, calcium, potassium, sulphate and phosphate. Dry land crops are cor-related with calcium, magnesium, chloride and, conse-quently, EC, phosphate and sulphate, and, vineyards are strongly correlated with high sulphate and phosphate levels.
Acknowledgments The authors would like to thank the EDIA, S.A. for providing the data. The authors also acknowledge the funding provided by ICT (Institute of Earth Sciences), under contract with FCT (the Portuguese Science and Technology Foundation).
References
Adams S, Titus R, Pietersen K, Tredoux G, Harris C (2001) Hydrochemical characteristics of aquifers near Sutherland in the Western Karoo, South Africa. J Hydrol 241:91–103
Almeida C, Mendonc¸a J, Jesus MR, Gomes A (2000) Sistemas Aquı´feros de Portugal Continental [Aquifer Systems of Conti-nental Portugal]. Instituto da A´ gua/Centro de Geologia da Universidade de Lisboa
Aris AZ, Abdullah MH, Kim K (2007) Hydrogeochemistry of groundwater in Manukan Island, Sabah. Malaysian J Anal Sci 11:407–413
Basnyat P, Teeter L, Flynn K, Lockaby G (1999) Relationships between landscape characteristics and non-point source pollution inputs to coastal estuaries. Environ Manage 23:539–549. doi:10. 1007/s002679900208
Bowatte S, Tillman R, Carran A, Gillingham A (2006) Can phosphorus fertilisers alone increase levels of soil nitrogen in New Zealand hill country pastures? Nutr Cycl Agroecosyst 75:57–66. doi:10.1007/s10705-006-9011-4
Burkartaus M, Stoner J (2008) Nitrogen in groundwater associated with agricultural systems. In: Hatfield JL, Follett RF (eds) Nitrogen in the environment: sources, problems, and manage-ment. USDA-ARS/UNL Faculty, Lincoln, pp 177–202 Carpenter SR, Caraco NF, Correll DL, Howarth RW, Sharpley AN,
Smith VH (1998) Nonpoint pollution of surface waters with phosphorus and nitrogen. Ecol Appl 8:559–568. doi:10.1890/ 1051-0761(1998)008[0559:NPOSWW]2.0.CO;2
Chambel A, Ribeiro L, Nascimento J, Duque J (1999) Development and application of hydrochemical factorial indexes using prin-cipal component analysis in South Portuguese Zone in Alentejo (Portugal). In: Hydrogeology and land use management, Fen-dekova´ M, Fendek M (eds) XXIX IAH Congress, Bratislava, pp 409–413
Chambel A, Duque J, Matoso A, Orlando M (2006) Hidrogeologia em Portugal Continental [Hydrogeology in Continental Portugal]. In: Dura´n J (ed) Boletı´n Geolo´gico Y Minero, pp 163–185 Chambel A, Duque J, Nascimento J (2007) Regional study of hard
rock aquifers in Alentejo, south Portugal: methodology and results. In: Kra´sny´ J, Sharp JM (eds) IAH-SP Series. Taylor and Francis, pp 73–93
Costa AM, Pimentel NLV, Barbosa BP (2003) A Formac¸a˜o de Vale do Guizo e o bordo oriental da Bacia do Baixo Tejo entre Crato e Avis: dados preliminares [Vale de Guizo Formation and the eastern border of the Lower Tagus Watershed between Crato and Avis: preliminary data]. In: Cieˆncias Da Terra (UNL), Lisboa, no esp. V, CD-ROM, C24–C27
Duan L, Hao J, Xie S, Zhou Z, Ye X (2002) Determining weathering rates of soils in China. Geoderma 110:205–225. doi:10.1016/ S0016-7061(02)00231-8
Duque J, Almeida C (1998) Caracterizac¸ao hidroquı´mica do Sistema Aquı´fero dos Gabros de Beja [Hydrochemical characterization of the Aquifer System of the Gabbros of Beja]. In: 4o Congresso da A´ gua. Acta, Lisbon, CD–164
ERHSA (2001) Projecto Estudo dos Recursos Hı´dricos Subterraˆneos do Alentejo [Project Study of Groundwater Resources of Alentejo]. Comissa˜o de Coordenac¸a˜o da Regia˜o Alentejo, E´ vora Fialho A, Chambel A, Duque J (1998) Sistema Aquı´fero dos Gnaisses de E´ vora [Aquifer system of the Gnaisses of E´vora]. In: 4o Congresso da A´ gua. Comunicac¸o˜es, Lisbon, CD–10
Foster S, Hirata R, Gomes D, D’Elia M, Paris M (2002) Groundwater quality protection: a guide for water utilities, municipal author-ities, and environment agencies. The World Bank, Washington, D.C.
Gasith A, Resh VH (1999) Streams in Mediterranean climate regions: abiotic influences and biotic responses to predictable seasonal events. Annu Rev Ecol Syst. doi:10.1146/annurev.ecolsys.30.1.51
Glavan M, Pintar M (2010) Impact of point and diffuse pollution sources on nitrate and ammonium ion concentrations in the karst-influenced Temenica river. Fresenius Environ Bull 19:1005–1014
Glavan M, Mili V, Pintar M (2013) Finding options to improve catchment water quality-Lessons learned from historical land use situations in a Mediterranean catchment in Slovenia. Ecol Modell 261–262:58–73. doi:10.1016/j.ecolmodel.2013.04.004
Griffith JA (2002) Geographic techniques and recent applications of remote sensing to landscape-water quality studies. Water Air Soil Pollut 138:181–197
Guo H, Wang Y (2004) Hydrogeochemical processes in shallow quaternary aquifers from the northern part of the Datong Basin, China. Appl Geochemistry 19:19–27. doi: 10.1016/S0883-2927(03)00128-8
Hecke T Van (2012) Power study of ANOVA versus Kruskal–Wallis test. J Stat Manag Syst 15:241–247. doi:10.1080/09720510. 2012.10701623
Kolpin DW (1997) Agricultural chemicals in groundwater of the midwestern United States: relations to land use. J Environ Qual 26:1025–1037. doi:10.2134/jeq1997.00472425002600040014x
Lerner DN, Harris B (2009) The relationship between land use and groundwater resources and quality. Land use policy 26:S265– S273. doi:10.1016/j.landusepol.2009.09.005
Lin CY, Abdullah MH, Praveena SM, Yahaya AHB, Musta B (2012) Delineation of temporal variability and governing factors influencing the spatial variability of shallow groundwater chemistry in a tropical sedimentary island. J Hydrol 432–433:26–42. doi:10.1016/j.jhydrol.2012.02.015
Matson PA (1997) Agricultural intensification and ecosystem prop-erties. Science 277:504–509. doi:10.1126/science.277.5325.504
Menezes JPC De, Bertossi APA, Santos AR, Neves MA (2014) Correlac¸a˜o entre uso da terra e qualidade da a´gua sub-terraˆnea [Correlation between land use and groundwater qual-ity]. Eng. Sanit. e Ambient. 19:173–186. doi: 10.1590/S1413-41522014000200008
Morais M (1995) Organizac¸a˜o espacial e temporal de um rio tempora´rio Mediterraˆneo (rio Degebe, Bacia Hidrogra´fica do Guadiana) [Spatial and temporal organisation of a Mediter-ranean temporary river (river Degebe, Guadiana Hydrographic Watershed)]. Univeristy of E´ vora
Morais M, Pinto P, Guilherme P, Rosado J, Antunes I (2004) Assessment of temporary streams: the robustness of metric and multimetric indices under different hydrological conditions. Hydrobiologia 516:229–249. doi:10.1023/B:HYDR. 0000025268.66163.32
Morgenstern U, Daughney C (2012) Groundwater age for identifica-tion of baseline groundwater quality and impacts of land-use intensification—The National Groundwater Monitoring Pro-gramme of New Zealand. J Hydrol 456–457:79–93. doi:10. 1016/j.jhydrol.2012.06.010
Pacheco FAL (1998) Application of correspondence analysis in the assessment of groundwater chemistry. Math Geol 30(2):129–161. doi:10.1029/96WR01683
Pacheco FAL, Landim PMB (2005) Two-way regionalized classifi-cation of multivariate data sets and its appliclassifi-cation to the assessment of hydrodynamic dispersion. Math Geol 37(4):393–417. doi:10.1007/s11004-005-5955-1
Pacheco FAL, Szocs T (2006) ‘‘Dedolomitization Reactions’’ driven by anthropogenic activity on loessy Sediments, SW Hungary. Appl Geochem 21:614–631. doi:10.1016/j.apgeochem.2005.12.009
Pacheco FAL, Van der Weijden CH (1996) Contributions of water-rock interactions to the composition of groundwater in areas with sizeable anthropogenic input. A case study of the waters of the Funda˜o area, central Portugal. Water Resour Res 32(12):3553–3570. doi:10.1029/96WR01683
Pacheco FAL, Van der Weijden CH (2002) Mineral weathering rates calculated from spring water data: a case study in an area with intensive agriculture, the Morais massif, NE Portugal. Appl Geochem 17(5):583–603. doi:10.1016/S0883-2927(01)00121-4
Pacheco FAL, Van der Weijden CH (2012a) Weathering of plagio-clase across variable flow and solute transport regimes. J Hydrol 420–421:46–58. doi:10.1016/j.jhydrol.2011.11.044
Pacheco FAL, Van der Weijden CH (2012b) Integrating topography, hydrology and rock structure in weathering rate models of spring watersheds. J Hydrol 428–429:32–50. doi:10.1016/j.jhydrol. 2012.01.019
Pacheco FAL, Van der Weijden CH (2014a) Modeling rock weathering in small watersheds. J Hydrol 513C:13–27. doi:10. 1016/j.jhydrol.2014.03.036
Pacheco FAL, Van der Weijden CH (2014b) Role of hydraulic diffusivity in the decrease of weathering rates over time. J Hydrol 512:87–106. doi:10.1016/j.jhydrol.2014.02.041
Pacheco FAL, Sousa Oliveira A, Van der Weijden AJ, Van der Weijden CH (1999) Weathering, biomass production and groundwater chemistry in an area of dominant anthropogenic influence, the Chaves-Vila Pouca de Aguiar region, north of Portugal. Water Air Soil Pollut 115(1/4):481–512. doi:10.1023/ A:1005119121666
Pacheco FAL, Landim PMB, Szocs T (2013) Anthropogenic impacts on mineral weathering: a statistical perspective. Appl Geochem 36:34–48. doi:10.1016/j.apgeochem.2013.06.012
PGBH (2012) Plano de Gesta˜o das Bacias Hidrogra´ficas integradas na Regia˜o Hidrogra´fica 7 [Management plan of the hydrographic watersheds integrated in the hydrographic region 7]. Adminis-trac¸a˜o Regional, Ministe´rio da Agricultura, Mar, Ambiente e Ordenamento Territorial
Rademacher LK, Clark JF, Hudson GB, Erman DC, Erman NA (2001) Chemical evolution of shallow groundwater as recorded by springs, Sagehen basin; Nevada County, California. Chem Geol 179:37–51. doi:10.1016/S0009-2541(01)00314-X
Ribeiro L (2009) A´ guas subterraˆneas [Groundwater]. In: Pereira H, Domingos T, Vicente L, Proenc¸a V (eds) Ecossistemas e Bem-Estar Humano em Portugal, Avaliac¸ao para Portugal do Millennium Ecossystem Assessment. Escolar Editora, Lisbon, pp 381–411 Rosado J, Morais M (2010) Climate change and water scarcity: from a
global scale to particular aspects in Mediterranean region (Portugal). In: Sens L, Mondardo R (eds) Science and Technol-ogy for Environmental Studies—experiences from Brazil, Portu-gal and Germany. Federal University of Santa Catarina, pp 15–27 Roth NE, Allan JD, Erickson DL (1996) Landscape influences on stream biotic integrity assessed at multiple spatial scales. Landsc Ecol 11:141–156. doi:10.1007/BF02447513
Rusjan S, Brilly M, Mikosˇ M (2008) Flushing of nitrate from a forested watershed: an insight into hydrological nitrate mobi-lization mechanisms through seasonal high-frequency stream nitrate dynamics. J Hydrol 354:187–202. doi:10.1016/j.jhydrol. 2008.03.009
Santos RMB, Sanches Fernandes LF, Moura JP, Pereira MG, Pacheco FAL (2014) The impact of climate change, human interference, scale and modeling uncertainties on the estimation of aquifer properties and river flow components. J Hydrol 519:1297–1314. doi:10.1016/j.jhydrol.2014.09.001
Santos RMB, Sanches Fernandes LF, Varandas SGP, Pereira MG, Sousa R, Teixeira A, Lopes-Lima M, Cortes RMV, Pacheco FAL (2015) Impacts of climate change and land-use scenarios on Margaritifera margaritifera, an environmental indicator and endangered species. Sci Total Environ 511:477–488. doi:10. 1016/j.scitotenv.2014.12.090
Serafim A, Morais M, Guilherme P, Sarmento P, Ruivo M, Magric¸o A (2006) Spatial and temporal heterogeneity in the Alqueva reservoir, Guadiana river, Portugal. Limnetica 25:771–786 Silva H, Morais M, Rosado J, Serafim A, Pedro A, Sarmento P, Fialho
A (2011) South Portugal Reservoirs—Status and major concerns. In: The 12 th International Specialized Conference on Watershed
and River Basin Management. International Water Association (IWA), Recife, p 8
SNIRH (2012) Sistema Nacional de Informac¸a˜o de Recursos Hı´dri-cos [National information system on water resources]
Soveral Dias J (1999) Co´digo de Boas Pra´ticas Agrı´colas [Code of Good Agriculture Practices]. Laborato´rio Quı´mico-Agrı´cola Rebelo da Silva
Stigter TY, Carvalho Dill AMM, Ribeiro L, Reis E (2006) Impact of the shift from groundwater to surface water irrigation on aquifer dynamics and hydrochemistry in a semi-arid region in the south of Portugal. Agric Water Manag 85:121–132. doi:10.1016/j. agwat.2006.04.004
Treidel H, Martin-bordes JL, Gurdak J (2012) Climate change effects on groundwater resources. CRC Press, Taylor and Francis Group, London
Valle Junior RF, Varandas SGP, Sanches Fernandes LF, Pacheco FAL (2014) Groundwater quality in rural watersheds with
environmental land use conflicts. Sci Total Environ 493:812–827. doi:10.1016/j.scitotenv.2014.06.068
Van der Weijden CH, Pacheco FAL (2006) Hydrogeochemistry in the Vouga river basin (central Portugal): pollution and chemical weathering. Appl Geochem 21:580–613. doi:10.1016/j.apgeo chem.2005.12.006
Vijith H, Satheesh R (2007) Geographical Information System based assessment of spatiotemporal characteristics of groundwater quality of upland sub-watersheds of Meenachil River, parts of Western Ghats, Kottayam District, Kerala, India. Environ Geol. 53:1–9. doi:10.1007/s00254-006-0612-7
Yang Q, Meng F-R, Zhao Z, Chow TL, Benoy G, Rees HW, Bourque CP-A (2009) Assessing the impacts of flow diversion terraces on stream water and sediment yields at a watershed level using SWAT model. Agric Ecosyst Environ 132:23–31. doi:10.1016/j. agee.2009.02.012
